Transactions on Neural Systems and Rehabilitation Engineering

Featured Articles
Deep Pinsker and James-Stein Neural Networks for Decoding Motor Intentions from Limited Data
Non-parametric regression has been shown to be useful in extracting relevant features from Local Field Potential (LFP) signals for decoding motor intentions. Yet, in many instances, brain-computer interfaces (BCIs) rely on simple classification methods, circumventing deep neural networks (DNNs) due... Read more
Featured Articles
Mining Within-Trial Oscillatory Brain Dynamics to Address the Variability of Optimized Spatial Filters
   Data-driven spatial filtering algorithms optimize scores, such as the contrast between two conditions to extract oscillatory brain signal components. Most machine learning approaches for the filter estimation, however, disregard within-trial temporal dynamics and are extremely sensitive to changes in training... Read more